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Amazon Bedrock AgentCore Runtime now supports stateful MCP server features Amazon Bedrock AgentCore Runtime now supports stateful Model Context Protocol (MCP) server features, enabling developers to build MCP servers that leverage elicitation, sampling, and progress notifications alongside existing support for resources, prompts, and tools. These capabilities allow MCP servers deployed to AgentCore Runtime to collect user input interactively during tool execution, request LLM-generated content from clients, and provide real-time progress updates for long-running operations. With stateful MCP sessions, each user session runs in a dedicated microVM with isolated resources, and the server maintains session context across multiple interactions using an Mcp-Session-Id header. Elicitation enables server-initiated, multi-turn conversations to gather information such as user preferences. Sampling allows servers to request AI-powered text generation from the client for tasks like personalized recommendations. Progress notifications keep clients informed during operations such as searching for flights or processing bookings. These features work together to support complex, interactive agent workflows that go beyond simple request-response patterns. Stateful MCP server features are supported in AgentCore Runtime across fourteen AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Canada (Central), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), and Europe (Stockholm). To learn more, see Stateful MCP server features in the Amazon Bedrock AgentCore documentation.

🆕 Amazon Bedrock AgentCore Runtime now supports stateful MCP server features, enabling interactive, multi-turn workflows with elicitation, sampling, and real-time progress updates across fourteen AWS regions.

#AWS #AmazonBedrock

Amazon Bedrock now supports observability of First Token Latency and Quota Consumption Amazon Bedrock is a fully managed service for building generative AI applications using high-performing foundation models from leading AI providers. It now supports two new CloudWatch metrics, TimeToFirstToken and EstimatedTPMQuotaUsage, giving you deeper visibility into inference performance and quota consumption. TimeToFirstToken measures the latency from when a request is sent to when the first token is received, for streaming APIs (ConverseStream and InvokeModelWithResponseStream). You can use this metric to set CloudWatch alarms which monitor latency degradation and establish SLA baselines, without any client-side instrumentation. EstimatedTPMQuotaUsage tracks your estimated Tokens Per Minute (TPM) quota consumption, including cache write tokens and output burndown multipliers, across all inference APIs (Converse, InvokeModel, ConverseStream, and InvokeModelWithResponseStream). You can use this metric to set proactive alarms before reaching your quota limit, track your quota consumption across your models, and request further quota increases before usage is rate limited. Both metrics are supported in all commercial Bedrock regions for models available via cross-region inference profiles and in-region inference, updated every minute for successfully completed requests. These are available in your CloudWatch out of the box; you pay only for the underlying model inference you consume, with no API changes or opt-in required. To learn more about TimeToFirstToken and EstimatedTPMQuotaUsage, see our documentation page on Monitoring Amazon Bedrock.

🆕 Amazon Bedrock now offers observability with new CloudWatch metrics: TimeToFirstToken for latency and EstimatedTPMQuotaUsage for quota consumption, enhancing performance monitoring and proactive quota management across all commercial regions without additional setup.

#AWS

AWS Builder ID now supports Sign in with GitHub and Amazon AWS Builder ID, your profile for accessing AWS applications including AWS Builder Center, AWS Training and Certification and Kiro, now supports two new social logins: GitHub and Amazon. This expansion of sign-in options builds on the existing Google Apple social sign-in capabilities, providing GitHub and Amazon users with a streamlined way to access AWS resources without managing separate credentials on AWS. With Sign in with Github and Amazon integration, developers and builders can now enjoy access to their AWS Builder ID profile using their GitHub or Amazon Account credentials. This enhancement eliminates password management complexity, reduces forgotten password issues, and provides a frictionless experience for both new user registration and returning user sign-ins. Whether you're accessing development resources in AWS Builder Center, enrolling in certification programs or using Kiro to code your next app, your GitHub and Amazon Accounts can now serve as a secure gateway to your builder AWS journey. To learn more about AWS Builder ID and get started with Sign in with GitHub and Amazon, visit the AWS Builder ID documentation.

🆕 AWS Builder ID now supports GitHub and Amazon sign-ins, providing streamlined access for developers via their accounts, reducing password hassles and improving user experience across AWS Builder Center, Training, and Certification, and Kiro.

#AWS #AwsIamIdentityCenter

Amazon Connect enhances AI-powered predictive insights Today, Amazon Connect is announcing enhancements to AI-powered predictive insights that make it easier for businesses to deliver proactive, personalized customer experiences at scale. Building on the five recommendation algorithms launched at re:Invent 2025, AI-powered predictive insights now support up to 40 million product catalog items (8X increase), are available in message templates for trigger-based campaigns, and deliver up to 14% improved model accuracy. These enhancements enable businesses to automatically engage customers with the right message at the right time, while reducing the time required to deploy AI-powered personalization. Businesses can now deliver trigger-based campaigns to initiate personalized outreach based on customer behavior and predictive signals – such as sending product recommendations when a customer abandons their cart or offering complementary services after a purchase. Businesses can now deliver targeted campaigns for specific customer cohorts based on predicted preferences and behaviors. Improved model accuracy and reduced training time mean businesses can deploy personalized experiences faster with greater confidence in the recommendations provided to customers. With Amazon Connect Customer Profiles, you only pay-as-you-go for utilized profiles. Public preview for AI-powered predictive insights enhancements is available in Europe (Frankfurt), US East (N. Virginia), Asia Pacific (Seoul), Asia Pacific (Tokyo), US West (Oregon), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central). To learn more, visit our webpages for Customer Profiles and explore the AI-powered predictive insights documentation.

🆕 Amazon Connect boosts AI-powered predictive insights for proactive, personalized customer experiences at scale, supporting 40M items, trigger-based campaigns, and 14% improved accuracy. Pay-as-you-go profiles available; public preview in multiple regions.

#AWS #AmazonConnect

Amazon SageMaker Unified Studio now supports faster data preview in Visual ETL Amazon SageMaker Unified Studio introduces data preview v2.0 for Visual ETL, a new data preview mode that delivers near-instant results when building and iterating on visual ETL jobs. With data preview v2.0, data engineers and analysts can see the output of each transform in about one second, with no session startup required and at no additional compute cost. Data preview v2.0 uses an in-browser query engine to load and process data locally, removing the dependency on server-side Spark sessions for preview operations. Source data is fetched once and cached in the browser, so subsequent transforms apply instantly without re-querying the underlying data source. For Amazon Redshift users, this means you can iterate on transforms without additional queries against your Redshift cluster, keeping your preview workflow fast and your cluster resources focused on production workloads. Data preview v2.0 supports CSV, Parquet, and JSON files from Amazon S3, in addition to data from Amazon Redshift, Amazon S3 Tables, AWS Glue Data Catalog, and third-party sources including Snowflake, MySQL, PostgreSQL, SQL Server, Oracle, Google BigQuery, Amazon DynamoDB, and Amazon DocumentDB. A toggle in the Visual ETL editor gives you the option to switch between data preview v2.0 and the original Spark-based preview at any time. Data preview v2.0 in Visual ETL is available in all AWS Regions where Amazon SageMaker Unified Studio is supported. To learn more, visit the Amazon SageMaker Unified Studio documentation.

🆕 Amazon SageMaker Unified Studio's v2.0 data preview speeds up Visual ETL, delivering near-instant transform results in one second. It uses an in-browser query engine, caches data, and supports CSV, Parquet, JSON, and multiple sources. Available in all AWS Regions.

#AWS #AmazonSagemaker

Amazon OpenSearch Service now supports in-place volume increases for all volume sizes Amazon OpenSearch Service now extends in-place cluster volume size increases to volumes exceeding 3 TiB. With this enhancement, you can scale storage capacity across all volume sizes without requiring a blue/green deployment. Previously, you could perform volume increases up to 3 TiB on your clusters without a blue/green deployment. This release removes that limitation, making it easier for you to scale up quickly even beyond 3 TiB when required. Domains that already have a volume size above 3 TiB will require a blue/green deployment the first time a volume increase is made; subsequent volume increases will not require a blue/green deployment. Decreasing storage volume size, or making volume increases within short intervals, will still require a blue/green deployment. You can use the dry-run option to check whether your change requires a blue/green deployment. This feature is available in all AWS Commercial and AWS GovCloud (US) Regions where Amazon OpenSearch Service is available. See here for a full list of our Regions. To learn more about Amazon OpenSearch Service configurations, visit the documentation page.

🆕 Amazon OpenSearch Service lets you scale volumes over 3 TiB in-place, simplifying growth without blue/green deployments. For smaller volumes, a blue/green deployment is needed initially. Available in all regions where OpenSearch Service operates.

#AWS #AmazonOpensearchService

Amazon Route 53 Global Resolver is now generally available Today, AWS announced the general availability of Amazon Route 53 Global Resolver, an internet-reachable anycast DNS resolver that delivers easy, secure, and reliable DNS resolution for authorized clients from anywhere. Global Resolver is now available across 30 AWS Regions, with support for both IPv4 and IPv6 DNS query traffic. Previewed at re:Invent 2025 in 11 AWS Regions, Global Resolver gives authorized clients in your organization anycast DNS resolution of public internet domains and private domains associated with Route 53 private hosted zones — from any location. It also provides DNS query filtering to block potentially malicious domains, not-safe-for-work domains, and domains associated with advanced DNS threats such as DNS tunneling and Domain Generation Algorithms (DGA), along with centralized query logging. With general availability, Global Resolver adds protection against Dictionary DGA threats. New customers can explore Global Resolver with a 30-day free trial. For pricing and feature details, visit the service page. To see supported AWS Regions, see the region table. To get started, see the documentation.

🆕 AWS announced the general availability of Amazon Route 53 Global Resolver, an anycast DNS resolver offering secure, reliable DNS resolution across 30 regions, with IPv4/IPv6 support, DNS filtering, and query logging. Free trial available.

#AWS #AmazonRoute53

Amazon Connect now supports conversational analytics for email Amazon Connect now supports conversational analytics for email contacts, enabling contact center managers to automatically categorize emails, redact personally identifiable information (PII), and generate contact summaries. This allows you to quickly identify emerging trends, better maintain compliance by protecting sensitive information, and reduce the time spent reviewing agent performance. For example, when customers email about account issues, Amazon Connect automatically categorizes the email, redacts sensitive information, and generates a summary for supervisor review. To enable this feature, add the Set recording, analytics and processing behavior block to your flows before an email contact is assigned to your agent or sent to your end customer. You can customize which PII types to redact, choose whether redacted content shows specific PII type indicators e.g., [SSN] or generic markings ([PII]), opt to store both original and redacted versions in separate storage, as well as enable contact summaries. Using these analytics, you can quickly create rules to automatically trigger actions such as assigning categories, creating tasks, or updating cases. Amazon Connect conversational analytics is available in the US East (N. Virginia), US West (Oregon), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), and Europe (London) regions. To learn more and get started, please refer to the help documentation or visit the Amazon Connect website.

🆕 Amazon Connect now supports email analytics, categorizing, redacting PII, and summary generation for trends and compliance. Add analytics blocks to flows for automatic actions. Available in multiple regions. For details, visit Amazon Connect help or website.

#AWS #AmazonConnect

Amazon Connect introduces AI-powered manager assistance (Preview) Today, Amazon Connect announces the preview of an AI-powered assistant that enables contact center managers to get instant answers to operational questions using natural language. You can query across 150+ Amazon Connect metrics, including agent scheduling, self-service experience, and performance evaluations, with historical data for all of these, and receive results in seconds—eliminating hours of manual data gathering. The assistant can also diagnose underlying issues, such as identifying which queues are at risk of missing service level targets and recommending specific recovery actions. This feature is available as a preview. To request access, contact your AWS account team or an AWS Representative. To learn more about Amazon Connect, the AWS cloud-based contact center, visit the Amazon Connect website.

🆕 Amazon Connect launches AI-powered manager assistance preview, offering instant answers to operational queries via natural language, diagnosing issues, and recommending actions, all without manual data gathering. Request access via AWS account team.

#AWS #AmazonConnect

Amazon Quick Suite launches User Preferences for chat personalization We are announcing User Preferences in Amazon Quick Suite – a new feature that gives users greater control over how Quick looks, feels, and works for them. With User Preferences, users can now customize their Chat panel layout by setting it to open expanded or collapsed by default; Quick also automatically remembers their last used setting and resumes from where they left off. Users can select a default chat agent and pre-select a default knowledge scope for My Assistant, so their preferred agent is ready each time they return to Quick. Users can also personalize their experience by letting Quick know what to call them and sharing their area of focus at work – Quick uses this context to personalize responses and make interactions more relevant. Finally, users can view and manage their memories directly from User Preferences. Previously, users had no way to persist their preferred Chat settings, agent selection, or personal context across sessions. User Preferences addresses this by giving users a single place to configure how Quick works for them, saving time and making every interaction feel more personalized from the start. User Preferences is available in all AWS Regions where Amazon Quick Suite is available. To learn more, visit the Amazon Quick Suite User Guide.

🆕 Amazon Quick Suite introduces User Preferences for chat personalization, allowing users to customize layouts, default agents, and personal contexts to enhance their experience and save settings across sessions. Available globally where Quick Suite operates.

#AWS

Amazon EC2 G7e instances now available in Asia Pacific (Seoul) and Europe (Spain) regions Starting today, Amazon EC2 G7e instances accelerated by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs are now available in  Asia Pacific (Seoul) and Europe (Spain) regions. G7e instances offer up to 2.3x inference performance compared to G6e. Customers can use G7e instances to deploy large language models (LLMs), agentic AI models, multimodal generative AI models, and physical AI models. G7e instances offer the highest performance for spatial computing workloads as well as workloads that require both graphics and AI processing capabilities. G7e instances feature up to 8 NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, with 96 GB of memory per GPU, and 5th Generation Intel Xeon processors. They support up to 192 virtual CPUs (vCPUs) and up to 1600 Gbps of networking bandwidth. G7e instances support NVIDIA GPUDirect Peer to Peer (P2P) that boosts performance for multi-GPU workloads. Multi-GPU G7e instances also support NVIDIA GPUDirect Remote Direct Memory Access (RDMA) with EFA in EC2 UltraClusters, reducing latency for small-scale multi-node workloads. You can use G7e instances for Amazon EC2 in the following AWS Regions: US West (Oregon), US East (N. Virginia, Ohio), Europe (Spain) and Asia Pacific (Tokyo, Seoul). You can purchase G7e instances as On-Demand Instances, Spot Instances, or as part of Savings Plans. To get started, visit the AWS Management Console, AWS Command Line Interface (CLI), and AWS SDKs. To learn more, visit G7e instances.

🆕 Amazon EC2 G7e instances with RTX PRO 6000 GPUs are now available in Asia Pacific (Seoul) and Europe (Spain). These instances offer up to 2.3x inference performance, ideal for large language models and spatial computing workloads, with up to 192 vCPUs and 1600 Gbps networking.

#AWS #AmazonEc2

IAM Roles Anywhere now supports post-quantum digital certificates AWS Identity and Access Management (IAM) Roles Anywhere now supports the FIPS 204 Module-Lattice Digital Signature Standard (ML-DSA), a quantum-resistant digital signature algorithm standardized by the National Institute of Standards and Technology (NIST) to help protect against threat actors in possession of a large-scale quantum computer. ML-DSA is particularly valuable for IAM Roles Anywhere customers who authenticate workloads to AWS using X.509 certificates issued by certificate authorities, where a weakened signature algorithm could allow an unintended user to issue certificates and obtain unauthorized access. IAM Roles Anywhere enables workloads running outside of AWS to obtain temporary AWS credentials using X.509 certificates to access AWS resources. You establish trust between your AWS environment and your public key infrastructure (PKI) by creating a trust anchor, either by referencing your AWS Private Certificate Authority or registering your own certificate authorities (CAs) with IAM Roles Anywhere. You can now use ML-DSA-signed CA certificates as IAM Roles Anywhere trust anchors, and issue end entity certificates bound to ML-DSA keys. This feature is available in all AWS Regions where IAM Roles Anywhere is available, including the AWS GovCloud (US) Regions, AWS European Sovereign Cloud (Germany) Region, and China Regions. To learn more, see the IAM Roles Anywhere User Guide.

🆕 AWS IAM Roles Anywhere now supports post-quantum ML-DSA certificates for quantum-resistant signatures, letting workloads get temporary AWS credentials via X.509, boosting security against quantum threats. Available globally.

#AWS #AwsIdentityAndAccessManagement #AwsIam

Amazon Cognito is now available in Asia Pacific (Taipei) and Asia Pacific (New Zealand) Regions Amazon Cognito is now available in the AWS Asia Pacific (Taipei) and Asia Pacific (New Zealand) Regions. This launch introduces all Amazon Cognito features and tiers, allowing customers to implement secure sign-in and access control for users, AI agents, and microservices in minutes. For a full list of regions where Amazon Cognito is available, refer to the AWS Region Table. To learn more about Amazon Cognito, refer to Developer Guide, Product Detail Page, and Pricing Detail Page.

🆕 Amazon Cognito is now in Asia Pacific (Taipei) and (New Zealand), providing secure sign-in for users, AI, and microservices. For regions, see AWS Region Table. More details in Developer Guide, Product, and Pricing pages.

#AWS #AmazonCognito

Amazon CloudWatch Logs announces increased query concurrency and API limits Amazon CloudWatch Logs customers can now run up to 100 concurrent queries per account and execute 10 StartQuery and GetQueryResults API calls per second per account/per-region, using the Logs Insights Query Language (Logs Insights QL). These limit increases enable customers to support more users and execute more concurrent queries. With concurrency increasing from 30 to 100, more users can simultaneously run queries and leverage dashboards using Logs Insights QL. Customers using StartQuery and GetQueryResults APIs for Logs Insights QL benefit from higher limits without being throttled, enabling them to execute more queries and view results faster. The limit increases for Logs Insights queries is available in US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Canada (Central), Canada (Calgary), South America (São Paulo), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Europe (Milan), Europe (Zurich), Europe (Spain), Africa (Cape Town), Middle East(Tel Aviv), Asia Pacific (Mumbai), Asia Pacific (Hyderabad), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Melbourne), Asia Pacific (Tokyo), Asia Pacific (Osaka), Asia Pacific (Seoul), Asia Pacific (Hong Kong), Asia Pacific (Jakarta), Asia Pacific (Bangkok), Asia Pacific (Malaysia), Asia Pacific (Auckland), Asia Pacific (Taipei), and Mexico (Querétaro). For more information, visit the  Amazon CloudWatch Logs documentation.

🆕 Amazon CloudWatch Logs boosts query concurrency to 100 per account and API calls to 10/sec, enabling more users to run queries and view results faster across 26 regions. For details, see Amazon CloudWatch Logs documentation.

#AWS #AmazonCloudwatch #AmazonCloudwatchLogs

Amazon Redshift introduces new array functions for semi-structured data processing Amazon Redshift now supports nine new array functions for working with semi-structured data stored in the SUPER data type. The new functions include ARRAY_CONTAINS, ARRAY_DISTINCT, ARRAY_EXCEPT, ARRAY_INTERSECTION, ARRAY_POSITION, ARRAY_POSITIONS, ARRAY_SORT, ARRAY_UNION, and ARRAYS_OVERLAP, enabling you to search, compare, sort, and transform arrays directly within your SQL queries. Previously, performing these operations required writing complex custom PartiQL SQL logic. These functions simplify complex data transformations and reduce query complexity by enabling sophisticated array operations in a single SQL statement. For example, you can use ARRAY_CONTAINS and ARRAY_POSITION for element lookup, ARRAY_INTERSECTION and ARRAY_EXCEPT for set operations, or ARRAY_SORT and ARRAY_DISTINCT to organize and deduplicate data. These functions are particularly valuable for applications involving nested data structures, event processing, and analytics workflows where data needs to be aggregated, filtered, or transformed at scale. The new Amazon Redshift array functions are available in all AWS Regions, including the AWS GovCloud (US) Regions, where Amazon Redshift is available. To learn more, please visit our documentation.

🆕 Amazon Redshift adds nine new array functions for SUPER data type, simplifying semi-structured data processing with operations like ARRAY_CONTAINS, ARRAY_SORT, and ARRAY_UNION, reducing complex custom SQL logic and enhancing data transformation in SQL queries.

#AWS #AmazonRedshift

Amazon SageMaker Unified Studio adds light mode support for IAM-based domains Today, AWS announces light mode support in Amazon SageMaker Unified Studio for IAM-based domains. Customers can now configure the visual interface mode to match their preference, choosing between dark and light themes. Light mode helps improve readability in bright environments and provides a familiar visual experience for customers who prefer lighter interfaces. Combined with the existing dark mode, this update gives you full control over your development environment's appearance, improving accessibility and reducing eye strain across varying lighting conditions. In SageMaker Unified Studio settings, you can click on 'customize appearance' under your Profile settings to choose between visual modes including dark and light. The setting persists across browsers and devices. This feature is available in all regions where Amazon SageMaker Unified Studio is available. To learn more, refer to the User Guide.

🆕 AWS adds light mode support in Amazon SageMaker Unified Studio for IAM-based domains, letting users choose between dark and light themes for improved readability and accessibility. Available in all regions, settings persist across browsers and devices.

#AWS #AmazonSagemaker

Amazon Redshift introduces reusable templates for COPY operations Amazon Redshift now supports templates for the COPY command, allowing you to store and reuse frequently used COPY parameters. This new feature enables you to create reusable templates that contain commonly utilized formatting parameters, eliminating the need to manually specify parameters for each COPY operation. Templates help maintain consistency across data ingestion operations that use the COPY command. They also reduce the time and effort required to execute COPY commands. You can create standardized configurations for different file types and data sources, ensuring consistent parameter usage across your teams and reducing the likelihood of errors caused by manual input. When parameters need to be updated, changes to the template automatically apply to all future uses, simplifying maintenance and improving operational efficiency. Support for templates for the COPY command is available in all AWS Regions, including the AWS GovCloud (US) Regions, where Amazon Redshift is available. To get started with templates, see the documentation or check out the AWS Blog.

🆕 Amazon Redshift now offers reusable templates for COPY operations, allowing users to store and reuse common parameters, ensuring consistency, reducing manual input, and simplifying maintenance across all AWS Regions.

#AWS #AmazonRedshift

Amazon EventBridge Scheduler now provides a higher default quota for the CreateSchedule API Amazon EventBridge Scheduler now has a higher default service quota for the CreateSchedule API action. The default CreateSchedule request rate quota is now 5,000 requests per second in 11 AWS Regions. Quotas can be further increased to tens of thousands of requests per second by making a request through the Service Quotas console. EventBridge Scheduler is a serverless scheduler that allows you to create, run, and manage billions of scheduled events and tasks, across more than 270 AWS services, without provisioning or managing the underlying infrastructure. EventBridge Scheduler supports one-time and recurring schedules that can be created using cron expressions, rate expressions, or specific times with support for time zones and daylight savings. With today's increase to the default CreateSchedule quota, customers with high-throughput schedule creation workloads can operate at increased scale without needing to request a quota increase, reducing friction when onboarding new workloads or scaling existing ones. Scheduler will scale to the new quota automatically. You can request increases beyond the new default service quota in the Service Quotas console. View EventBridge Scheduler service quotas for each Region in the service endpoints and quotas documentation or learn more about the EventBridge Scheduler service in the EventBridge Scheduler documentation. The increased quota is now available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Ireland), South America (São Paulo), Asia Pacific (Mumbai), Europe (Frankfurt), Europe (London), Asia Pacific (Tokyo), Asia Pacific (Singapore), and Asia Pacific (Sydney) Regions.

🆕 Amazon EventBridge Scheduler boosts default CreateSchedule API quota to 5,000 requests/sec in 11 regions. Scheduler scales automatically; higher quotas available via Service Quotas console. Supports billions of scheduled tasks across 270+ AWS services.

#AWS

Amazon Redshift Serverless now maintains datashare permissions during restore Amazon Redshift Serverless now preserves datashare permissions when you restore a snapshot to the same namespace, simplifying data sharing workflows and reducing administrative overhead. Previously, restoring a serverless namespace from a snapshot required administrators to manually re-grant datashare permissions to consumer clusters and recreate consumer databases, even when restoring to the same namespace. With this enhancement, datashare permissions are automatically maintained when you restore a snapshot to the same producer namespace, provided the datashare permission existed both when the snapshot was taken and on the current namespace. For consumer namespaces, datashare access remains unchanged after restore, eliminating the need for producer administrators to re-grant permissions. This streamlines disaster recovery and testing workflows by reducing manual configuration steps and potential errors. Amazon Redshift also provides EventBridge notifications to alert you when datashares are dropped, consumer access is revoked, or public accessibility changes during restore operations. This feature is available in all AWS Regions that support Amazon Redshift. To learn more, see the Amazon Redshift Management Guide.

🆕 Amazon Redshift Serverless preserves datashare permissions during restores, simplifying workflows and cutting admin tasks. It maintains permissions when restoring snapshots within the same namespace, eliminating manual re-granting, and is available in all AWS Regions suppor…

#AWS #AmazonRedshift

Amazon EC2 R8g instances now available in additional regions Starting today, Amazon Elastic Compute Cloud (Amazon EC2) R8g instances are available in AWS Middle East (UAE), AWS Mexico (Central), and AWS Europe (Zurich) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 R8g instances are ideal for memory-intensive workloads such as databases, in-memory caches, and real-time big data analytics. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. AWS Graviton4-based R8g instances offer larger instance sizes with up to 3x more vCPU (up to 48xlarge) and memory (up to 1.5TB) than Graviton3-based R7g instances. These instances are up to 30% faster for web applications, 40% faster for databases, and 45% faster for large Java applications compared to AWS Graviton3-based R7g instances. R8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 R8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

🆕 Amazon EC2 R8g instances now available in UAE, Mexico, and Zurich regions. Powered by Graviton4, they offer up to 30% better performance than Graviton3-based instances, ideal for memory-intensive workloads. Available in 12 sizes, including bare metal, with enhanced networking.

#AWS #AmazonEc2

OpenSearch OR2 and OM2 instances in AWS GovCloud (US-East, US-West) Regions Amazon OpenSearch Service, expands availability of OR2 and OM2, OpenSearch Optimized Instance family to 12 additional regions. The OR2 instance delivers up to 26% higher indexing throughput compared to previous OR1 instances and 70% over R7g instances. The OM2 instance delivers up to 15% higher indexing throughput compared to OR1 instances and 66% over M7g instances in internal benchmarks The OpenSearch Optimized instances, leveraging best-in-class cloud technologies like Amazon S3, to provide high durability, and improved price-performance for higher indexing throughput better for indexing heavy workload. Each OpenSearch Optimized instance is provisioned with compute, local instance storage for caching, and remote Amazon S3-based managed storage. OR2 and OM2 offers pay-as-you-go pricing and reserved instances, with a simple hourly rate for the instance, local instance storage, as well as the managed storage provisioned. OR2 instances come in sizes ‘medium’ through ‘16xlarge’, and offer compute, memory, and storage flexibility. OM2 instances come in sizes ‘large’ through ‘16xlarge’ Please refer to the Amazon OpenSearch Service pricing page for pricing details. OR2 and OM2 instance family is now available on Amazon OpenSearch Service across 2 additional regions: AWS GovCloud (US-East, US-West).

🆕 Amazon OpenSearch Service now offers OR2 and OM2 instances in AWS GovCloud (US-East, US-West), providing up to 26% higher indexing throughput than OR1 and 70% over R7g instances, with pay-as-you-go and reserved pricing.

#AWS #AmazonOpensearchService

Amazon EC2 I8ge instances now generally available in Europe (Ireland) AWS region. Amazon Web Services (AWS) announces the availability of Amazon EC2 I8ge instances in Europe (Ireland) AWS region. Designed for large storage I/O intensive workloads, these new instances are powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, offering up to 40% better compute performance and 20% better price performance over existing I3en instances. I8ge instances offer up to 120TB local NVMe storage density—the highest available in the cloud for storage optimized instances—and deliver up to twice as many vCPUs and memory compared to prior generation instances. Powered by 3rd generation AWS Nitro SSDs, these instances achieve up to 65% better real-time storage performance, up to 50% lower storage I/O latency, and 65% lower storage I/O latency variability compared to I3en instances. Additionally, the 16KB torn write prevention feature, enables customers to eliminate performance bottlenecks for database workloads. I8ge instances are high-density storage-optimized instances, for workloads that demand rapid local storage with high random read/write performance and consistently low latency for accessing large data sets. These versatile instances are offered in eleven different sizes including 2 metal sizes, providing flexibility to match customers computational needs. They deliver up to 180 Gbps of network performance bandwidth, and 60 Gbps of dedicated bandwidth for Amazon Elastic Block Store (EBS), ensuring fast and efficient data transfer for the most demanding applications. To begin your Graviton journey, visit the Level up your compute with AWS Graviton page. To get started, see AWS Management Console, AWS Command Line Interface (AWS CLI), and AWS SDKs. To learn more, visit the I8ge instances page.

🆕 AWS now offers EC2 I8ge instances in Europe (Ireland), featuring 5th gen Intel Xeon processors, up to 120TB NVMe storage, and 65% better storage performance for large I/O workloads. Available in 11 sizes, these instances offer up to 180 Gbps network bandwidth.

#AWS #AmazonEc2

Database Savings Plans now supports Amazon OpenSearch Service and Amazon Neptune Analytics Today, AWS announces expanded coverage for Database Savings Plans, with support for Amazon OpenSearch Service and Amazon Neptune Analytics. With Database Savings Plans, you can save up to 35% in exchange for a commitment to a consistent amount of usage (measured in $/hour) over a one-year term with no upfront payment. Database Savings Plans automatically applies to eligible serverless and provisioned instance usage regardless of supported engine, instance family, size, deployment option, or AWS Region. For example, with Database Savings Plans, you can change from m7i.large.search to c8g.2xlarge.search within OpenSearch Service, or scale Neptune Analytics workloads while continuing to benefit from the discounted pricing. Database Savings Plans for Amazon OpenSearch Service and Amazon Neptune Analytics is available starting today in all AWS Regions, except China Regions. You can get started with Database Savings Plans from the AWS Billing and Cost Management Console or by using the AWS CLI. To realize the largest savings, you can make a commitment to Savings Plans by using purchase recommendations provided in the console. For a more customized analysis, you can use the Savings Plans Purchase Analyzer to estimate potential cost savings for custom purchase scenarios. For more information, visit the Database Savings Plans pricing page and the AWS Savings Plans FAQs.

🆕 AWS offers Database Savings Plans for OpenSearch and Neptune Analytics, saving up to 35% with a one-year commitment. Available globally except China, for serverless and provisioned instances. Start via AWS Billing console or CLI.

#AWS

Amazon EC2 M8g instances now available in additional regions Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M8g instances are available in Africa (Cape Town), Asia Pacific (Malaysia), Europe (Milan, Zurich), and Canada West (Calgary) regions. These instances are powered by AWS Graviton4 processors and deliver up to 30% better performance compared to AWS Graviton3-based instances. Amazon EC2 M8g instances are built for general-purpose workloads, such as application servers, microservices, gaming servers, midsize data stores, and caching fleets. These instances are built on the AWS Nitro System, which offloads CPU virtualization, storage, and networking functions to dedicated hardware and software to enhance the performance and security of your workloads. AWS Graviton4-based Amazon EC2 instances deliver the best performance and energy efficiency for a broad range of workloads running on Amazon EC2. These instances offer larger instance sizes with up to 3x more vCPUs and memory compared to Graviton3-based Amazon M7g instances. AWS Graviton4 processors are up to 40% faster for databases, 30% faster for web applications, and 45% faster for large Java applications than AWS Graviton3 processors. M8g instances are available in 12 different instance sizes, including two bare metal sizes. They offer up to 50 Gbps enhanced networking bandwidth and up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). To learn more, see Amazon EC2 M8g Instances. To explore how to migrate your workloads to Graviton-based instances, see AWS Graviton Fast Start program and Porting Advisor for Graviton. To get started, see the AWS Management Console.

🆕 Amazon EC2 M8g instances are now available in new regions, offering up to 30% better performance with AWS Graviton4 processors, larger sizes, and enhanced networking. Ideal for general-purpose workloads, they improve performance and security via the Nitro System.

#AWS #AmazonEc2

AWS Shield network security director findings are now available in AWS Security Hub Today, AWS Shield announces findings from network security director, currently in preview, are now available in AWS Security Hub. AWS Shield network security director identifies missing or misconfigured network security services like AWS WAF, VPC security groups, and VPC network access control lists (ACLs) in your AWS Organization and provides remediation recommendations. Network security director findings now also appear in the Inventory section of the Security Hub console. With network security director, you can continuously analyze your network across accounts or organizational units in your AWS Organization, and receive findings highlighting missing or misconfigured network security services per AWS best practices. The severity of each finding is determined based on a combination of the misconfiguration identified and the network topology of the resource the finding is associated with. To learn more, visit the overview page.

🆕 AWS Shield's network security director findings are now in AWS Security Hub, highlighting misconfigured services and offering fixes. They appear in the Inventory section, aiding network security analysis across accounts.

#AWS #AwsShield #AwsSecurityHub

Multi-party approval now supports approval team baselining Multi-party approval (MPA) now supports MPA administrators running test approvals to confirm that their approval team is set up correctly and that approvers are active and reachable. With this new capability, customers ensure their approval teams do not become unresponsive due to natural attrition, incorrect approver selection, or reduced engagement. MPA administrators and security teams can now proactively assess their approval configurations before relying on them for sensitive operations. The baseline feature enables proactive team health management by allowing manual initiation of test approval sessions through the AWS Organizations console. Customers can verify approver availability, identify inactive team members, and maintain compliance with internal governance requirements. Key use cases include regular team responsiveness verification, recommended every 90 days by AWS using the MPA Console, onboarding validation for new approval configurations, and operation health checks to ensure approval workflows function effectively when needed. This feature is available in all AWS commercial regions. To learn more about implementing baseline testing for your multi-party approval workflows, visit the Multi-party approval documentation.

🆕 AWS Multi-party approval now verifies approver availability and responsiveness for compliance and readiness, available in all commercial regions. It supports proactive health checks and onboarding validations. For details, see the Multi-party approval documentation.

#AWS #AwsOrganizations

AWS Elastic Beanstalk now offers AI-powered environment analysis AWS Elastic Beanstalk now offers AI-powered environment analysis to help you quickly identify root causes and get recommended solutions for environment health issues. When your environment experiences problems, Elastic Beanstalk collects recent events, instance health, and logs from your environment and sends them to Amazon Bedrock for analysis. This feature is designed for developers and operations teams who need to diagnose and resolve environment issues faster without manually reviewing logs and events. You can request an AI analysis directly from the Elastic Beanstalk console using the AI Analysis button when your environment's health status is Warning, Degraded, or Severe. You can also use the AWS CLI with the RequestEnvironmentInfo and RetrieveEnvironmentInfo API operations. The analysis provides step-by-step troubleshooting recommendations tailored to your environment's current state, helping you reduce mean time to resolution. AI-powered environment analysis is available in all AWS Regions where both AWS Elastic Beanstalk and Amazon Bedrock are available.  For more information about the AI-powered environment analysis and for a full list of supported platform versions, see the Elastic Beanstalk developer guide. To learn more about Elastic Beanstalk, visit the Elastic Beanstalk product page.

🆕 AWS Elastic Beanstalk now uses AI to quickly diagnose issues and suggest fixes through Amazon Bedrock. Available everywhere, it analyzes events, instance health, and logs for faster troubleshooting.

#AWS #AwsElasticBeanstalk

Introducing Amazon Connect Health, Agentic AI Built for Healthcare Amazon Connect Health is now generally available, bringing purpose-built agentic AI to healthcare organizations to streamline patient engagement and point-of-care workflows. Amazon Connect Health delivers five AI agents designed to reduce administrative burden across the care continuum — enabling patients faster access to care and freeing clinicians from paperwork and administrative burden to focus on what matters most: their patients. These agents are ready to deploy within existing patient, clinician, and healthcare workflows — such as patient access centers (i.e., contact centers), Electronic Health Records (EHR) applications, and telehealth solutions — in days, not months. All the features follow responsible AI best practices, implement safety guardrails, are HIPAA-eligible, and deliver the same security and reliability standards as any AWS service. Agents available at launch: Patient verification (GA) – Confirms patient identity in real time against EHR records with appointment lookup, reducing inbound call-handling time. Appointment management (Preview) – Books appointments via natural language voice interaction, 24/7, with real-time insurance eligibility checks, enabling after-hours scheduling, and relieving burden on human staff.  Patient insights (Preview) – Surfaces relevant patient history and clinical context before the visit, so clinicians walk in prepared. Reduces the time clinicians spend piecing together information before a patient’s visit. Ambient documentation (GA) – Captures patient-clinician conversations during the visit and generates clinical notes in real time. Medical coding (Preview) – Automatically generates ICD-10 and CPT codes from clinical notes post-visit, with full audit trails. Amazon Connect Health patient engagement capabilities are natively integrated with Amazon Connect, a complete AI-powered contact center solution delivering personalized customer experiences at scale. Clinical and administrative staff can configure and customize these AI capabilities in minutes using the Amazon Connect Health application, enabling rapid testing and seamless deployment into contact center workflows. The point-of-care capabilities — ambient listening, patient insight, and medical coding — are available via Amazon Connect Health unified SDK (SDK documentation), enabling developers to integrate the features directly into existing EHR and clinician-facing applications.    Amazon Connect Health is available in US East (N. Virginia) and US West (Oregon). To get started, visit the Amazon Connect Health product page. For technical details, see the Amazon Connect Health documentation

🆕 Amazon Connect Health deploys AI agents to streamline healthcare workflows, cutting admin tasks and boosting patient access. Key features: real-time verification, 24/7 booking, ambient docs, and coding. HIPAA-eligible, integrates with Amazon Connect, ready in days. Available…

#AWS #AmazonConnect

Amazon OpenSearch Service introduces capacity optimized blue/green deployments Amazon OpenSearch Service now offers a Capacity Optimized option for blue/green deployments, ensuring domain updates can complete even when available instance capacity is less than required. Updates are performed in incremental batches, reducing the number of additional instances needed during the process. Amazon OpenSearch Service uses a blue/green deployment process when updating domains — creating an idle copy of the original environment, applying updates, and routing traffic to the new environment once complete. This minimizes downtime and preserves the original environment as a fallback. Until now, blue/green deployments required 100% instance capacity upfront. For example, for a cluster with 100 data nodes, another 100 nodes were needed to proceed. If sufficient capacity was unavailable, customers had to wait and retry later. Now, customers can choose between two deployment strategies. The default Full Swap option maintains current behavior, requiring full capacity upfront for the fastest deployment. The new Capacity Optimized option attempts a full capacity deployment first, but automatically falls back to batch deployment if capacity is insufficient. OpenSearch Service determines the appropriate batch size based on cluster size and available instances. Because updates are applied in batches, this option may take longer than a full-swap deployment. Customers can select their preferred option in the deployment configuration settings via the OpenSearch Service console or API. We recommend choosing the Capacity Optimized deployment option for clusters with 30 or more nodes. The Capacity Optimized option is available for all OpenSearch and Elasticsearch versions, across all AWS Commercial Regions where OpenSearch Service is available. See here for a full listing of our Regions. To learn more, visit the documentation page.

🆕 Amazon OpenSearch Service now supports Capacity Optimized blue/green deployments, allowing domain updates with insufficient capacity by applying changes in batches. This reduces extra instances and offers two strategies: Full Swap and Capacity Optimized.

#AWS #AmazonOpensearchService

AWS HealthLake announces data transformation agent for automated CCDA-to-FHIR data conversion (Preview) Starting today, healthcare organizations can now transform legacy clinical documents into queryable FHIR resources in AWS HealthLake in days instead of months, unlocking use cases such as longitudinal patient record generation, population health analytics, and clinical data exchange. AWS HealthLake data transformation agent (preview) is an AI-powered capability that converts Consolidated Clinical Document Architecture (CCDA) files into Fast Health Interoperability Resources Release 4 (FHIR R4)-compliant resources without requiring specialized FHIR expertise, through an integrated experience that combines real-time conversion testing, AI-assisted template customization, and scalable bulk import. The data transformation agent includes ready-to-use templates for CCDA 2.1 to FHIR R4 data conversion. Developers can submit individual CCDA files through a synchronous conversion API or console workflow and receive transformed FHIR Bundles in seconds. They can preview results, interactively validate conversion quality, and sign off on templates before production use. An enhanced import workflow automatically detects uploaded CCDA files, applies the active template, matches and reconciles patients based on identifiers, and ingests the resulting FHIR resources into the target AWS HealthLake datastore with detailed logs. All capabilities are available both on the AWS console and programmatically via API for seamless integration into existing workflows. When default templates need adjustment, the data transformation agent offers an AI-powered experience to customize them directly in the console. Users can describe changes such as "skip medications with status entered-in-error" or "map procedure dates to performedDateTime instead of performedPeriod" in natural language, and the AI agent modifies the underlying template automatically. Manual curation is also available for power users who wish to make targeted template edits. Users can then immediately test against sample files, iterate conversationally, and publish once satisfied. AWS HealthLake is available in the US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Europe West (London), Europe (Ireland), and Asia Pacific SouthEast (Sydney) Regions. Visit the AWS Region Table to see all the regions. To learn more, see the AWS HealthLake product page.

🆕 AWS HealthLake introduces a data transformation agent to quickly convert CCDA to FHIR, enabling faster patient record generation and analytics. AI-powered, it offers customizable templates, bulk import, and seamless API integration, available in multiple regions.

#AWS #AmazonHealthlake